Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

Digital service analysis and design : the role of process modelling

Digital libraries are evolving from content-centric systems to person-centric systems. Emergent services are interactive and multidimensional, associated systems multi-tiered and distributed. A holistic perspective is essential to their effective analysis and design, for beyond technical considerations, there are complex social, economic, organisational, and ergonomic requirements and relationships to consider. Such a perspective cannot be gained without direct user involvement, yet evidence suggests that development teams may be failing to effectively engage with users, relying on requirements derived from anecdotal evidence or prior experience. In such instances, there is a risk that services might be well designed, but functionally useless. This paper highlights the role of process modelling in gaining such perspective. Process modelling challenges, approaches, and success factors are considered, discussed with reference to a recent evaluation of usability and usefulness of a UK National Health Service (NHS) digital library. Reflecting on lessons learnt, recommendations are made regarding appropriate process modelling approach and application

Wireless body sensor networks for health-monitoring applications

This is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. The publisher is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Quality-aware model-driven service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services

Towards the Model-Driven Engineering of Secure yet Safe Embedded Systems

We introduce SysML-Sec, a SysML-based Model-Driven Engineering environment aimed at fostering the collaboration between system designers and security experts at all methodological stages of the development of an embedded system. A central issue in the design of an embedded system is the definition of the hardware/software partitioning of the architecture of the system, which should take place as early as possible. SysML-Sec aims to extend the relevance of this analysis through the integration of security requirements and threats. In particular, we propose an agile methodology whose aim is to assess early on the impact of the security requirements and of the security mechanisms designed to satisfy them over the safety of the system. Security concerns are captured in a component-centric manner through existing SysML diagrams with only minimal extensions. After the requirements captured are derived into security and cryptographic mechanisms, security properties can be formally verified over this design. To perform the latter, model transformation techniques are implemented in the SysML-Sec toolchain in order to derive a ProVerif specification from the SysML models. An automotive firmware flashing procedure serves as a guiding example throughout our presentation.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201